Automation Workflow for Wholesale Capacity Pricing and Allocation

Static wholesale contracts leave revenue on the table during peak demand. This workflow uses reinforcement learning agents to set dynamic prices based on real-time network load, competitor benchmarks, and MVNO willingness-to-pay. By moving from fixed-fee to market-driven pricing, operators capture the true value of their spectrum and compute assets, directly improving wholesale margin.

Manual capacity allocation and service activation for MVNOs can take days. The workflow automates this via API orchestration: once a price is accepted, agents trigger provisioning hooks into the OSS/BSS stack (e.g., Nokia NSP, Ericsson ENM), RAN Intelligent Controller (RIC), and policy systems (PCRF) to instantiate the slice or dedicated bearer. This reduces operational overhead and accelerates time-to-revenue for new wholesale deals.

Over-allocating wholesale capacity can degrade retail customer experience. The workflow's forecasting agents analyze historical traffic, calendar events, and real-time telemetry to predict congestion hotspots 4-6 hours out. It then automatically adjusts wholesale allocations or recommends offload to alternative bands (e.g., shifting MVNO traffic to DSS-enabled spectrum) to protect KPI SLAs and avoid costly violations.

Manual reconciliation of resource usage against billing is error-prone and leaks revenue. The workflow embeds metering agents that collect granular, slice-level consumption data (PRB usage, compute cycles) and automatically generate auditable records. These feed directly into the billing/charging system (e.g., AMDOCS, Netcracker) for accurate, dispute-free settlement, closing the revenue assurance loop.

Fully autonomous pricing carries regulatory and strategic risk. The architecture includes configurable approval gates where proposed prices or allocations exceeding predefined bounds (e.g., a floor/ceiling, or impacting a high-priority enterprise slice) are routed to a human-in-the-loop dashboard built in tools like ServiceNow or a custom React frontend. All agent decisions are logged with full rationale for governance.

The workflow's value is unlocked by deep integration. It connects via APIs to: Network Inventory (for capacity visibility), RIC/xApps (for enforcement), Charging Systems (CBBS), and external Spectrum Trading Platforms. This turns the RAN into a liquid, tradable asset. Implementation uses an orchestration layer like Camunda or LangGraph to manage stateful flows across these heterogeneous systems.

This foundational component ingests live telemetry from RAN elements (vDU/vCU, radios), OSS performance data, and external demand signals (e.g., MVNO subscription forecasts, event calendars). AI agents fuse this data to create a real-time, predictive view of available sellable capacity and expected demand pressure, forming the basis for all pricing and allocation decisions. Integration with RAN Intelligent Controllers (RICs) and network analytics platforms is critical for low-latency, accurate data.

The core decision agent applies multi-factor pricing algorithms that consider spot network utilization, contractual minimums, competitor benchmark rates, MVNO credit tier, and forecasted scarcity. Algorithms range from reinforcement learning for yield optimization to rule-based engines for compliance. This component outputs a continuously updated price sheet and recommended allocation quotas, integrated with the carrier's wholesale billing (BSS) and product catalog systems for rate publication.

Upon a wholesale order or automated bid acceptance, this agentic layer triggers the technical fulfillment. It translates the commercial agreement (e.g., 100 Mbps guaranteed, best-effort slice) into network commands via APIs. This involves dynamic network slice instantiation via the 5G Core (NSSF, NRF), spectrum allocation adjustments via the RIC, and QoS policy updates (PCRF/PCF). Integration with Service Management and Orchestration (SMO) frameworks and OSS provisioning systems ensures zero-touch activation.

The customer-facing interface where MVNOs or enterprise buyers can view available capacity, real-time pricing, and place orders. A custom API gateway exposes capacity and pricing feeds for integration into MVNO's own systems, enabling automated procurement. This component handles authentication, quota management, and order validation, feeding directly into the pricing engine and provisioning hooks. It must enforce rate limits and commercial policy rules defined by the carrier's wholesale team.

A critical oversight layer that operates in parallel to the dynamic workflow. Agents continuously reconcile network resource consumption (measured via mediation systems) with billed usage from the BSS to prevent revenue leakage. It also monitors for SLA breaches on guaranteed slices and ensures all dynamic pricing and allocation actions adhere to regulatory spectrum sharing rules (e.g., CBRS, LSA) and internal governance policies, triggering alerts for human review.

The central orchestrator (built on frameworks like LangGraph or Temporal) manages the stateful workflow across all components, handling retries, failures, and rollbacks. It incorporates mandatory approval gates for out-of-band pricing changes or capacity allocations that exceed pre-defined risk thresholds, routing requests to wholesale operations teams via ITSM tools like ServiceNow. All decisions, rationales, and actions are logged to an immutable audit trail for explainability and post-analysis.